In TDMA radio communication systems (TDMA=Time Division Multiple Access) and other frame based communication systems information is transmitted on a channel in the form of signal frames or bursts. In order to synchronize the receiver to these signal frames each signal frame comprises a known synchronization word in a predetermined position within each signal frame. In for instance the European GSM system for mobile telephony this synchronization word is 26 bits long. When the receiver expects a new signal frame from the transmitter, a training sequence that is identical to the transmitted synchronization word is generated by a training sequence generator in the receiver. The received signals are compared to the locally generated training sequence, and when the best possible correlation is obtained between this sequence and the received signals, synchronization is considered to exist between the locally generated and the received signal.
In addition to the synchronization itself the training sequence is also used for channel estimation. Since the radio channel often is subjected to multiple path propagation the receiver comprises some sort of equalizer to eliminate this phenomenon. The equalizer requires a time limited estimate of the impulse response of the channel. This impulse response can be obtained from the correlation signal. Forney 1! and Ungerboeck 2! describe two different algorithms that, given the channel impulse response and Gaussian channel noise with known correlation properties, determine the most likely sent sequence. Both algorithms will work properly, but with degraded performance, if an approximate estimate of the channel impulse response is used instead of the true impulse response, or if the noise is non-Gaussian. The equalizer makes use of the channel estimate to initialize and update e.g. filter taps. An example is the Maximum Likelihood Sequence Estimation (MLSE) detector, where an FIR-filter is used directly as a model of the channel 2!. Another example is decision feedback equalizers (DFE) 4!, where the filter taps in both forward and feed-back are calculated from the channel estimate.
When the channel is estimated from a received synchronization word the estimate will contain noise, since the received data is noisy and the training sequence is of finite length. Even a channel estimate that is updated continuously will be noisy. The noise content in the channel estimate will be very high in e.g. fading dips, since the signal level in that case is low compared to the noise or interference level, giving a low signal-to-noise ratio in the received data. The synchronization process is also disturbed by receiver noise. An incorrect and unstable synchronization gives an incorrect channel estimate as a secondary effect, thereby causing a substantial loss in receiver performance. The noisy channel estimate gives incorrect settings for the filter taps in the detector or equalizer, e.g. the MLSE will have an incorrect FIR channel model. This causes degraded demodulation performance in a way similar to the degradation from noisy received samples. The effect is that the interference or noise in the received samples has a double impact--first the channel model is impaired, then the incorrectly set equalizer will have to equalize and demodulate noisy samples.
A common feature of the described prior art is that the channel estimate is used directly in the detection or equalization procedure without considering the noise content of the estimate. However, for example the MLSE is optimized in the sense that it gives the most likely demodulated symbol sequence only if the receiver noise is additive Gaussian and the channel estimate is exact. It is not optimal if there is noise in the channel estimate.
A method of reducing the influence of noisy taps in the channel estimate is proposed in U.S. Pat. No. 5,251,233 (Labedz et al). There it is suggested to delete taps in the channel estimate that are below a certain threshold value, thereby reducing the noise contribution from noisy taps with low content of useful signal. Totally eliminating some channel estimate taps may, however, remove vital information, since it is very difficult to distinguish between useful signal energy and noise energy in a tap.
EP-A-0 535 403 describes a method in which a channel estimate of a current burst is combined with a channel estimate of a previous burst. Both estimates have the same number of taps.